{"uid":"cap_lZ9HPWVtoZ28HTfw-6oVY","slug":"tablint-spreadsheet-preflight-inspector-591e36e6","name":"tablint Spreadsheet Preflight Inspector","description":"Inspect a CSV, TSV, or XLSX spreadsheet before an agent ingests it. Detects misplaced header rows, repeated header rows, multiple tables on one sheet, merged cells, ragged rows, totals rows, formulas, hidden sheets, mixed or inconsistent column types, numbers stored as text, ambiguous dates, and duplicate or empty column names. Returns a machine verdict (clean, needs cleaning, split tables, review, or reject), the blocking problems, per-sheet structure, per-column types, and a recommended next action so the agent knows whether the file is safe to load and what to fix first.","url":"https://tablint.dev/v1/bazaar/table/preflight","method":"GET","headers":{},"bodySchema":{"type":"object","properties":{"checks":{"type":"array","items":{"type":"string"},"description":"Checks to run; use [\"all\"] for the full preflight."},"file_url":{"type":"string","format":"uri","description":"Public https URL of a CSV, TSV, or XLSX file to inspect."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_nMInvzC9J9N_1FJPcpdO_","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Inspects a CSV, TSV, or XLSX file for structural problems and returns a machine-readable verdict plus actionable recommendations before an agent ingests it.","exampleAgentPrompt":"Before I load this data file, run a full preflight check on it — the file is at https://data.example.com/sales_q1.xlsx — and tell me if it's safe to ingest or what needs fixing first.","exampleUseCases":[{"title":"ETL pipeline safety gate","prompt":"Before we load this supplier data into our warehouse, can you run all the preflight checks on https://files.supplier.com/inventory_2024.csv and tell me if there are any blocking issues like ragged rows or duplicate column names?"},{"title":"Data analyst spreadsheet audit","prompt":"I just got this Excel report from finance and I want to know if it has any structural problems — merged cells, multiple tables, hidden sheets, that kind of thing — can you run a full preflight on https://internal.corp.com/q4_report.xlsx before I start analyzing it?"},{"title":"AI agent ingestion guard","prompt":"We're about to feed this CSV into our ML pipeline — please check https://datasets.myapp.com/training_data.tsv with all checks to see if column types are consistent and there are no totals rows or formulas that could corrupt the training run."}],"resultDescription":"Returns a machine verdict (one of: clean, needs cleaning, split tables, review, or reject), a list of blocking problems, per-sheet structural details, per-column type information, and a recommended next action indicating whether the file is safe to load and what to fix first.","failureModes":["File URL is not publicly accessible or returns a non-200 response","File format is not CSV, TSV, or XLSX","File is too large to inspect within timeout","Invalid or malformed URL provided","Network timeout fetching the remote file","Unsupported encoding or corrupted file contents"],"whenToPreferThis":"Use this endpoint before any agent pipeline ingests a user-supplied or third-party spreadsheet file. It is the right choice when you need a structured, machine-readable verdict on data quality rather than a human-readable summary, and when you want to catch structural issues (merged cells, ragged rows, multiple embedded tables, type inconsistencies) before they silently corrupt downstream processing. Prefer it over manual parsing attempts or generic file validators when the input format is CSV, TSV, or XLSX and you need actionable, per-column and per-sheet diagnostics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T06:38:08.792Z","isFirstParty":false}